1. Technical Field of the Invention
The present system relates to the measurement of wheel profiles and, more particularly, a non-contact method and apparatus capable of measuring wheel profiles while a train is in motion.
2. General Background
Large railroad operators, out of necessity, spend a considerable amount of time and money inspecting, repairing, and replacing railroad wheels. The inability to easily, accurately, and quickly identify and correct wheel problems is not only dangerous, since worn wheels are a major cause of derailments, but can also be costly due to the interruption of normal railroad operations while wheels are inspected and condemnable wheels (i.e., wheels with profiles that are out of tolerances) are replaced.
Regardless of the importance of identifying wheel problems, only about 5 percent of the railcar wheels in North America are fully inspected annually, due to the current difficulties in measuring profiles (such as manual use of gauges while a train is stopped).
Machine vision systems are one solution to the problem, because they can potentially enable automatic wayside profile measurements to be made as trains pass, without disrupting the normal operation of a railroad. In practice, however, machine vision systems have had limitations. For example, U.S. Pat. No. 5,793,492 (Vanaki) discloses a system that uses four “gage points” to estimate wheel circumference. The gage points Vanaki uses, however, are not points on the working surface of the wheel, so the system is incapable of determining the real working diameter of the wheel, and is also incapable of determining tread hollow, which is a critical indicator of condemnable wheels.
Another document, U.S. Pat. No. 5,247,338, discloses a contactless measurement system that requires advance knowledge of wheel size, stored in a database. The '338 patent requires wheel size data to be communicated to the measurement system prior to wheel measurement. Since the working diameter of wheels is not directly measured by the '338 patent's system, tread hollow cannot be accurately determined, and further, the system is adversely affected by variations in the vertical deflection of wheels due to different weight loads.
Bright ambient light can also present problems for some machine vision systems that rely on projected light to make measurements. A further limitation of some machine vision systems is the requirement that the relative positions of cameras and light sources must be set up precisely to ensure accurate results, which in turn requires time-consuming manual calibration. Another source of error of some systems is the relative position of the cameras and light sources with respect to the wheels when images are captured.
It would, therefore, be desirable to have an improved machine vision system that can make accurate, automatic measurements.